The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Este artigo propõe um esquema de quantização vetorial que permite considerar a dinâmica dos vetores de entrada. No esquema proposto, uma transformação linear é aplicada aos vetores de entrada consecutivos e o vetor resultante é quantizado com uma medida de distorção definida pelas estatísticas. No lado do decodificador, a sequência do vetor de saída é determinada usando as estatísticas associadas aos índices transmitidos de tal forma que a verossimilhança é maximizada. Para resolver o problema de maximização, um algoritmo computacionalmente eficiente é derivado. O desempenho do método proposto é avaliado na quantização de parâmetros LSP. Verifica-se que as trajetórias do LSP e os espectros correspondentes mudam suavemente no método proposto. Mostra-se também que a utilização do método proposto resulta em uma melhoria significativa da qualidade subjetiva.
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Kazuhito KOISHIDA, Keiichi TOKUDA, Takashi MASUKO, Takao KOBAYASHI, "Vector Quantization of Speech Spectral Parameters Using Statistics of Static and Dynamic Features" in IEICE TRANSACTIONS on Information,
vol. E84-D, no. 10, pp. 1427-1434, October 2001, doi: .
Abstract: This paper proposes a vector quantization scheme which makes it possible to consider the dynamics of input vectors. In the proposed scheme, a linear transformation is applied to the consecutive input vectors and the resulting vector is quantized with a distortion measure defined by the statistics. At the decoder side, the output vector sequence is determined using the statistics associated with the transmitted indices in such a way that a likelihood is maximized. To solve the maximization problem, a computationally efficient algorithm is derived. The performance of the proposed method is evaluated in LSP parameter quantization. It is found that the LSP trajectories and the corresponding spectra change quite smoothly in the proposed method. It is also shown that the use of the proposed method results in a significant improvement of subjective quality.
URL: https://global.ieice.org/en_transactions/information/10.1587/e84-d_10_1427/_p
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@ARTICLE{e84-d_10_1427,
author={Kazuhito KOISHIDA, Keiichi TOKUDA, Takashi MASUKO, Takao KOBAYASHI, },
journal={IEICE TRANSACTIONS on Information},
title={Vector Quantization of Speech Spectral Parameters Using Statistics of Static and Dynamic Features},
year={2001},
volume={E84-D},
number={10},
pages={1427-1434},
abstract={This paper proposes a vector quantization scheme which makes it possible to consider the dynamics of input vectors. In the proposed scheme, a linear transformation is applied to the consecutive input vectors and the resulting vector is quantized with a distortion measure defined by the statistics. At the decoder side, the output vector sequence is determined using the statistics associated with the transmitted indices in such a way that a likelihood is maximized. To solve the maximization problem, a computationally efficient algorithm is derived. The performance of the proposed method is evaluated in LSP parameter quantization. It is found that the LSP trajectories and the corresponding spectra change quite smoothly in the proposed method. It is also shown that the use of the proposed method results in a significant improvement of subjective quality.},
keywords={},
doi={},
ISSN={},
month={October},}
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TY - JOUR
TI - Vector Quantization of Speech Spectral Parameters Using Statistics of Static and Dynamic Features
T2 - IEICE TRANSACTIONS on Information
SP - 1427
EP - 1434
AU - Kazuhito KOISHIDA
AU - Keiichi TOKUDA
AU - Takashi MASUKO
AU - Takao KOBAYASHI
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E84-D
IS - 10
JA - IEICE TRANSACTIONS on Information
Y1 - October 2001
AB - This paper proposes a vector quantization scheme which makes it possible to consider the dynamics of input vectors. In the proposed scheme, a linear transformation is applied to the consecutive input vectors and the resulting vector is quantized with a distortion measure defined by the statistics. At the decoder side, the output vector sequence is determined using the statistics associated with the transmitted indices in such a way that a likelihood is maximized. To solve the maximization problem, a computationally efficient algorithm is derived. The performance of the proposed method is evaluated in LSP parameter quantization. It is found that the LSP trajectories and the corresponding spectra change quite smoothly in the proposed method. It is also shown that the use of the proposed method results in a significant improvement of subjective quality.
ER -